A Sublime Plugin, With Backend Service In Bottle, and Going Live Using OpenShift

A Sublime Plugin, With Backend Service In Bottle, and Going Live Using OpenShift

Dinesh Kumar (~dineshkumar-cse)
|
09 Apr, 2016

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Description:

In this session,

We'll create a Sublime Plugin which shares data, eg: Share code snippet with others. Sublime Plugin itself cannot have data (No Storage's associated with it, we have to store it in server so that anyone can access it), So we'll also create a service which saves/exposes the data, and the plugin will use the service.

Developing Backend Service (REST) & Hosting in OpenShift

REST Service convention and need of it

Creating REST Service with python bottle (microframework)

Integrating service with MongoDB (why NoSql DataBase is cool)

Introduction to OpenShift and its deployment Process

Deploying to OpenShift, Rewritting history in Git, as commit is the trigger for redeployment

Openshift is PAS, we can use other alternatives too like heroku or other. I've taken Openshift for workshop.

Creating Sublime Plugin

Sublime Plugin Development for Sublime Text Editor

Consume the service we built

How to publish our Plugin

Development Process

Using Git, Running sample Tests and Linters By Integrating with CI (Travis), Deploying it by other means like ansible

Prerequisites:

Software/Account

Insatll python3+ version, Install pyenv, virtualenv

git

An openshift account

Github account

Sublime Text Editor

Concept:

Basic understanding of python

Familiar with Git, pushing and pulling code

Basics of REST Service

Content URLs:

The Workshop is hands on, so its just code. I've shared two of plugin examples.

Github Links

Service Code: https://github.com/dineshkumar-cse/preferenceSyncService

Speaker Info:

I've worked in different Tech Stack, Python, Java, Ruby etc, and have used many frameworks, built applications end to end.
Have exposure to Test Driven Development, Continous Integration/Continous Delivery, Agile etc.
I am experimenting with Auto Pilot Drone, also learning Machine Learning, functional Programming